mmer 1.0.2

MMER: Multivariate Mixed Effects Regression.

MMER: Python Package for Multivariate Mixed Effects Regression

Overview

MMER is a Python package for multivariate mixed-effects regression featuring a modular fixed-effects component. It supports parametric and non-parametric machine learning regressors (neural networks, random forests, XGBoost), handles multiple responses and grouping factors, and provides direct access to the covariance matrices arising from its multivariate formulation [1].

Table of Contents

• Features and Installation
• User Guide
• License
• Contact
• References

Features and Installation

See the Documentation.

User Guide

The full documentation, including examples and the complete API reference, is available at mmer.readthedocs.io.

License

MMER is released under the MIT License.
See the LICENSE file for the full text.

Contact

For questions or assistance, please feelfree to contact:

S.M. Sajad Hussaini
📧 [e-mail]

Please include "MMER" in the subject line for a quicker response.

Support the Project

If you find this package useful, contributions to help maintain and improve it, are always appreciated.

References

Please cite the following references for any formal study:

[1] Primary Reference
A Multivariate Mixed-Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches
DOI: [To be added]
(Expected publication in the Journal of Earthquake Engineering and Structural Dynamics)

[2] MMER Package
MMER: Python Package for Multivariate Mixed Effects Regression
DOI: https://doi.org/10.5281/zenodo.18068839